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Sustainable automated data recovery: a research roadmap
| Content Provider | ACM Digital Library |
|---|---|
| Author | Bos, Jeroen van den |
| Abstract | Digital devices contain increasingly more data and applications. This means more data to handle and a larger amount of different types of traces to recover and consider in digital forensic investigations. Both present a challenge to data recovery approaches, requiring higher performance and increased flexibility. In order to progress to a long-term sustainable approach to automated data recovery, this paper proposes a partitioning into manual, custom, formalized and self-improving approaches. These approaches are described along with research directions to consider: building universal abstractions, selecting appropriate techniques and developing user-friendly tools. . |
| Starting Page | 6 |
| Ending Page | 9 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450351560 |
| DOI | 10.1145/3121252.3121254 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-09-04 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Data recovery Digital forensics Automated software engineering |
| Content Type | Text |
| Resource Type | Article |
